{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DEXPEfHQxZ-D"
   },
   "source": [
    "# Clipped Hyperbolic Classifiers Are Super-Hyperbolic Classifiers\n",
    "\n",
    "Welcome to our fourth notebook for the ECCV 2022 Tutorial \"[Hyperbolic Representation Learning for Computer Vision](https://sites.google.com/view/hyperbolic-tutorial-eccv22)\"!\n",
    "\n",
    "**Open notebook:** \n",
    "[![View on Github](https://img.shields.io/static/v1.svg?logo=github&label=Repo&message=View%20On%20Github&color=lightgrey)](https://github.com/MinaGhadimiAtigh/hyperbolic_representation_learning/blob/main/notebooks/4_Clipped_Hyperbolic_Classifiers_Are_Super_Hyperbolic_Classifiers.ipynb)\n",
    "[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MinaGhadimiAtigh/hyperbolic_representation_learning/blob/main/notebooks/4_Clipped_Hyperbolic_Classifiers_Are_Super_Hyperbolic_Classifiers.ipynb)  \n",
    "\n",
    "**Author:** Mina Ghadimi Atigh"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "72g1wtISdyxq"
   },
   "source": [
    "In this tutorial, you will go through [Clipped Hyperbolic Classifiers Are Super-Hyperbolic Classifiers](https://openaccess.thecvf.com/content/CVPR2022/papers/Guo_Clipped_Hyperbolic_Classifiers_Are_Super-Hyperbolic_Classifiers_CVPR_2022_paper.pdf), CVPR 2022 paper.\n",
    "\n",
    "While many datasets and labels are hierarchical in nature, Euclidean space is suboptimal in learning the hierarchical structures. Hyperbolic space is a non-Euclidean space with constant negative curvature. As moving from the origin towards the boundary, the distances grow exponentially, as in hierarchical structures. When the dataset contains a known hierarchical structure, projecting the Euclidean features to hyperbolic space improves the performance. Hyperbolic neural networks. However, HNN suffers from several limitations. \n",
    "<ul>\n",
    "<li> HNN underperforms ENN when the dataset does not have a hierarchical structure. </li>\n",
    "<li> There are some limitations even when the dataset contains hierarchical structure. </li>\n",
    "<li> HNNs performance on tandard benchmarks is not investigated. </li>\n",
    "</ul>\n",
    "\n",
    "Here you can see an example of a hybrid HNN, in which the embedding of the input is extracted with an ENN as the first step. Then, the embedding is projected to the hyperbolic space using Exponential Map and loss function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center width=\"100%\"><img src=\"figures/4_fig1.png\"></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "EVzDvDSXK1uR"
   },
   "source": [
    "## Vanishing gradients is the problem in hybrid HNN!\n",
    "\n",
    "The goal is to find out why HNNs underperform ENNs in some cases. The key element may be backpropagating the **gradients** from the hyperbolic space to the Euclidean space. So let's look at how gradients are calculated. \n",
    "\n",
    "\\begin{align}\n",
    "\\frac{\\partial \\ell}{\\partial w^E} = (\\frac{\\partial x^H}{\\partial w^E})^T\\frac{\\partial \\ell}{\\partial x^H}\n",
    "\\end{align}\n",
    "\n",
    "where $x^E$ and $x^H$ are the Euclidean and Hyperbolic embeddings of the input $x$. $\\frac{\\partial \\ell}{\\partial x^H}$ in the gradient of the loss function $\\ell$ with respect to the hyperbolic embedding $x^H$, which is the Riemannian gradient,\n",
    "\n",
    "\\begin{align}\n",
    "\\frac{\\partial \\ell}{\\partial x^H} = \\frac{(1 - \\|x^H\\|^2)^2}{4} \\nabla\\ell(x^H)\n",
    "\\end{align}\n",
    "\n",
    "where $\\nabla\\ell(x^H)$ is the Euclidean gradient.\n",
    "\n",
    "During training and learning embeddings in hyperbolic space, the points move to the boundary of the hyperbolic space, resulting in $\\|x^H\\|^2$ getting close to $1$. Consequently, the gradient diminishes during training, which indicates vanishing gradients as a problem occurring during the training of a hybrid HNN."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BqwtDz36qqOf"
   },
   "source": [
    "## How can we avoid vanishing gradients?\n",
    "Since approaching the boundary of hyperbolic space causes problems in training, one solution may be to impose a soft regularization on the Euclidean embedding before the exponential map so that the norm of the embedding does not exceed a certain threshold.\n",
    "\n",
    "\\begin{align}\n",
    "CLIP(x^E; r) = min\\{1, \\frac{r}{\\|x^E\\|}\\} . x^E\n",
    "\\end{align}\n",
    "\n",
    "where r is a hyperparameter. Also, clipped hyperbolic embedding will be $CLIP(x^H;r) = Exp_0^c(CLIP(x^E;r))$.\n",
    "\n",
    "\n",
    "As a result of clipping, hyperbolic embeddings will not lie throughout the hyperbolic space. Here you can see the clipped hybrid HNN."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center width=\"100%\"><img src=\"figures/4_fig2.png\"></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LTgASz4Js9qH"
   },
   "source": [
    "Here, you can find out the implementation of clipping, applied on top of Euclidean embedding. `clip(input_vector, r)` gets the Euclidean embedding and r which is the hyperparameter and outputs the clipped Euclidean embedding vector."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "Ax2gpkpNs9GA"
   },
   "outputs": [],
   "source": [
    "def clip(input_vector, r):\n",
    "    input_norm = torch.norm(input_vector, dim = -1)\n",
    "    clip_value = float(r)/input_norm\n",
    "    min_norm = torch.clamp(float(r)/input_norm, max = 1)\n",
    "    return min_norm[:, None] * input_vector"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ybpuAb4aqiif"
   },
   "source": [
    "## Clipped Hyperbolic Embeddings\n",
    "\n",
    "To check how the clipping affects the performance of HNN, we will go through [Notebook2, Hyperbolic Image Embessings](https://github.com/MinaGhadimiAtigh/hyperbolic_representation_learning/blob/main/notebooks/2_Hyperbolic_Image_Embeddings.ipynb). Everything is same as Notebook2 and the only difference is feeding the clipped Euclidean features to the hyperbolic space."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8qucLFCIGcMy"
   },
   "source": [
    "Let's start with importing libraries, setting manual seed and downloading *CUB-200-2011* Dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "bqsBtgrZOrdq",
    "outputId": "7162f3a0-36a6-4faf-f7fc-a2f8e3e0e0c3"
   },
   "outputs": [],
   "source": [
    "!wget -q https://raw.githubusercontent.com/leymir/hyperbolic-image-embeddings/6633edbbeffd6d90271f0963852a046c64f407d6/examples/fewshot/networks/convnet.py\n",
    "!pip install -q git+https://github.com/geoopt/geoopt.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "6csDjdMFOYIS"
   },
   "outputs": [],
   "source": [
    "## standard libraries\n",
    "import numpy as np\n",
    "import os\n",
    "import PIL\n",
    "from PIL import Image\n",
    "from PIL import ImageEnhance\n",
    "import random\n",
    "import warnings\n",
    "\n",
    "## Imports for plotting\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "## PyTorch\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "\n",
    "## PyTorch Torchvision\n",
    "import torchvision\n",
    "from torchvision import transforms\n",
    "\n",
    "## geoopt for hyperbolic  \n",
    "import geoopt\n",
    "\n",
    "## Neural network downloaded from paper's GitHub\n",
    "from convnet import ConvNet\n",
    "\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "SPfaAlH99dBr",
    "outputId": "771b0c0a-92aa-40f3-adef-328253eded4c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using device cuda:0\n"
     ]
    }
   ],
   "source": [
    "# Function for setting the seed\n",
    "def set_seed(seed):\n",
    "    np.random.seed(seed)\n",
    "    torch.manual_seed(seed)\n",
    "    if torch.cuda.is_available():\n",
    "        torch.cuda.manual_seed(seed)\n",
    "        torch.cuda.manual_seed_all(seed)\n",
    "set_seed(42)\n",
    "\n",
    "# Ensure that all operations are deterministic on GPU (if used) for reproducibility\n",
    "torch.backends.cudnn.determinstic = True\n",
    "torch.backends.cudnn.benchmark = False\n",
    "\n",
    "# Fetching the device that will be used throughout this notebook\n",
    "device = torch.device(\"cpu\") if not torch.cuda.is_available() else torch.device(\"cuda:0\")\n",
    "print(\"Using device\", device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "3u5f6fievwuD",
    "outputId": "3cc1829b-74e3-4f4a-e1da-50a5070a150d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mkdir: cannot create directory ‘split’: File exists\n",
      "/home/mina/workspace/hyperbolic_representation_learning/notebooks/data/cub/split\n",
      "/home/mina/workspace/hyperbolic_representation_learning/notebooks\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import clear_output \n",
    "%mkdir data\n",
    "%mkdir data/cub\n",
    "%cd data/cub\n",
    "!wget -q -O tmp.tgz https://data.caltech.edu/records/65de6-vp158/files/CUB_200_2011.tgz?download=1\n",
    "!tar -xzvf tmp.tgz\n",
    "!rm tmp.tgz\n",
    "!rm attributes.txt\n",
    "%mkdir images\n",
    "!mv CUB_200_2011/images/*/*.jpg images\n",
    "!mv CUB_200_2011/classes.txt classes.txt\n",
    "!rm -r CUB_200_2011\n",
    "clear_output()\n",
    "\n",
    "%mkdir split\n",
    "%cd split\n",
    "![ ! -f test.csv ] && wget -q https://raw.githubusercontent.com/leymir/hyperbolic-image-embeddings/master/examples/fewshot/data/cub/split/test.csv\n",
    "![ ! -f val.csv ] && wget -q https://raw.githubusercontent.com/leymir/hyperbolic-image-embeddings/master/examples/fewshot/data/cub/split/val.csv\n",
    "![ ! -f train.csv ] && wget -q https://raw.githubusercontent.com/leymir/hyperbolic-image-embeddings/master/examples/fewshot/data/cub/split/train.csv\n",
    "%cd ../../.."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yCJ53D7Md7zg"
   },
   "source": [
    "The next step is to handle data loader functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "QbSYQXtxnHnV"
   },
   "outputs": [],
   "source": [
    "# ROOT to the images and split, data files are available here.\n",
    "ROOT_PATH = os.getcwd()\n",
    "DATA_PATH = os.path.join(ROOT_PATH, \"data/cub/\")\n",
    "IMAGE_PATH = os.path.join(DATA_PATH, \"images\")\n",
    "SPLIT_PATH = os.path.join(DATA_PATH, \"split\")\n",
    "\n",
    "# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
    "transformtypedict = dict(\n",
    "    Brightness=ImageEnhance.Brightness,\n",
    "    Contrast=ImageEnhance.Contrast,\n",
    "    Sharpness=ImageEnhance.Sharpness,\n",
    "    Color=ImageEnhance.Color,\n",
    ")\n",
    "\n",
    "\n",
    "class ImageJitter(object):\n",
    "    def __init__(self, transformdict):\n",
    "        self.transforms = [(transformtypedict[k], transformdict[k]) for k in transformdict]\n",
    "\n",
    "    def __call__(self, img):\n",
    "        out = img\n",
    "        randtensor = torch.rand(len(self.transforms))\n",
    "        for i, (transformer, alpha) in enumerate(self.transforms):\n",
    "            r = alpha * (randtensor[i] * 2.0 - 1.0) + 1\n",
    "            out = transformer(out).enhance(r).convert(\"RGB\")\n",
    "        return out\n",
    "\n",
    "\n",
    "# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
    "\n",
    "# This is for the CUB dataset, which does not support the ResNet encoder now\n",
    "# It is notable, we assume the cub images are cropped based on the given bounding boxes\n",
    "# The concept labels are based on the attribute value, which are for further use (and not used in this work)\n",
    "class CUB(Dataset):\n",
    "    def __init__(self, setname):\n",
    "        txt_path = os.path.join(SPLIT_PATH, setname + \".csv\")\n",
    "        lines = [x.strip() for x in open(txt_path, \"r\").readlines()][1:]\n",
    "        data = []\n",
    "        label = []\n",
    "        lb = -1\n",
    "        self.wnids = []\n",
    "\n",
    "        for l in lines:\n",
    "            context = l.split(\",\")\n",
    "            name = context[0]\n",
    "            wnid = context[1]\n",
    "            path = os.path.join(IMAGE_PATH, name)\n",
    "            if wnid not in self.wnids:\n",
    "                self.wnids.append(wnid)\n",
    "                lb += 1\n",
    "\n",
    "            data.append(path)\n",
    "            label.append(lb)\n",
    "\n",
    "        self.data = data\n",
    "        self.label = label\n",
    "        self.num_class = np.unique(np.array(label)).shape[0]\n",
    "\n",
    "        normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
    "\n",
    "        if setname == \"train\":\n",
    "            self.transform = transforms.Compose([transforms.RandomResizedCrop(84),\n",
    "                                                 ImageJitter(dict(Brightness=0.4, Contrast=0.4, Color=0.4)),\n",
    "                                                 transforms.RandomHorizontalFlip(),\n",
    "                                                 transforms.ToTensor(),\n",
    "                                                 transforms.Normalize(np.array([0.485, 0.456, 0.406]),\n",
    "                                                                      np.array([0.229, 0.224, 0.225])),\n",
    "                                                 ])\n",
    "\n",
    "        else:\n",
    "            self.transform = transforms.Compose([transforms.Resize(84, interpolation=PIL.Image.BICUBIC),\n",
    "                                                 transforms.CenterCrop(84),\n",
    "                                                 transforms.ToTensor(),\n",
    "                                                 normalize, ])\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data)\n",
    "\n",
    "    def __getitem__(self, i):\n",
    "        path, label = self.data[i], self.label[i]\n",
    "        x = Image.open(path).convert(\"RGB\")\n",
    "        image = self.transform(Image.open(path).convert(\"RGB\"))\n",
    "        return image, label\n",
    "\n",
    "\n",
    "# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
    "class CategoriesSampler:\n",
    "    def __init__(self, label, n_batch, n_cls, n_per):\n",
    "        self.n_batch = n_batch\n",
    "        self.n_cls = n_cls\n",
    "        self.n_per = n_per\n",
    "\n",
    "        label = np.array(label)\n",
    "        self.m_ind = []\n",
    "        for i in range(max(label) + 1):\n",
    "            ind = np.argwhere(label == i).reshape(-1)\n",
    "            ind = torch.from_numpy(ind)\n",
    "            self.m_ind.append(ind)\n",
    "\n",
    "    def __len__(self):\n",
    "        return self.n_batch\n",
    "\n",
    "    def __iter__(self):\n",
    "        for i_batch in range(self.n_batch):\n",
    "            batch = []\n",
    "            classes = torch.randperm(len(self.m_ind))[: self.n_cls]\n",
    "            for c in classes:\n",
    "                l = self.m_ind[c]\n",
    "                pos = torch.randperm(len(l))[: self.n_per]\n",
    "                batch.append(l[pos])\n",
    "            batch = torch.stack(batch).t().reshape(-1)\n",
    "            yield batch\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "SyU1dgz2a0gO"
   },
   "source": [
    "Exctract class names of the CUB dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/mina/workspace/hyperbolic_representation_learning/notebooks/data/cub/'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DATA_PATH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "gCHUo2XObHRk"
   },
   "outputs": [],
   "source": [
    "classname_file = os.path.join(DATA_PATH, 'classes.txt')\n",
    "class_dict = {}\n",
    "with open(classname_file) as f:\n",
    "    lines = f.readlines()\n",
    "    for i, line in enumerate(lines):\n",
    "        class_num = int(line.split(' ')[0])\n",
    "        class_dict[class_num - 1] = line.split('.')[1].split('\\n')[0].replace('_', ' ')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XIvu81r5VuLk"
   },
   "source": [
    "Before starting the main task, let's check how images from the dataset look like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "oSDIoLDxZayh"
   },
   "outputs": [],
   "source": [
    "# define a sample trainset\n",
    "sample_trainset = CUB(\"train\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "FrKGPN02g6vx"
   },
   "outputs": [],
   "source": [
    "# number of images to plot\n",
    "NUM_IMAGES = 4\n",
    "# Index of images to plot\n",
    "indexes = random.sample(range(len(sample_trainset)), NUM_IMAGES)\n",
    "images = [sample_trainset[idx][0] for idx in indexes]\n",
    "labels = [sample_trainset[idx][1] for idx in indexes]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 234
    },
    "id": "FyYBjZL8WnaX",
    "outputId": "b7e6b6b8-cd2e-4779-a3cb-eef3974e972b"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Boat tailed Grackle  |  Brewer Blackbird  |  Brown Creeper     |  Clark Nutcracker\n"
     ]
    }
   ],
   "source": [
    "img_grid = torchvision.utils.make_grid(images, nrow=8, normalize=True, pad_value=0.9)\n",
    "img_grid = img_grid.permute(1, 2, 0)\n",
    "\n",
    "plt.figure(figsize=(12,8))\n",
    "plt.title(\"Examples of CUB dataset\")\n",
    "plt.imshow(img_grid)\n",
    "plt.axis('off')\n",
    "plt.show()\n",
    "plt.close()\n",
    "print('  |  '.join(f'{class_dict[labels[j]]:16s}' for j in range(NUM_IMAGES)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4WLYRpiPiRTj"
   },
   "source": [
    "## Clipped Few Shot learning in hyperbolic space"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kdpHPlb0jvHU"
   },
   "source": [
    "First, we set the value of hyperparameters, assigned using `Config`. The hyperparameters are set for 5-way 1-shot task (same as Notebook 2). \n",
    "\n",
    "Note that we train the model for 5 epochs, but to reproduce the final paper numbers, the model should be trained more.\n",
    "\n",
    "__What's new?__\n",
    "\n",
    "Two values are added to the `Config` to perform clipping. _First_, `do_clip` is used to show whether to use clipping or not. When `do_clip` is `False`, model will be same as Notebook2. _Second_, `r` is the hyperparameter used in $CLIP(x^E, r)$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "id": "mVy4wmo3jtgt"
   },
   "outputs": [],
   "source": [
    "class Config:\n",
    "    def __init__(self, shot=1, lr=0.001, step=50, gamma=0.8, c=0.05, model=\"convnet\", hyperbolic = True, dim=1600,\n",
    "                 query=15, way=5, validation_way=5, temperature=1, dataset=\"CUB\", lr_decay=True, max_epoch=200, \n",
    "                 do_clip = True, r = 1.0):\n",
    "        \n",
    "        self.lr = lr                                  # learning rate\n",
    "        self.lr_decay = lr_decay                      # Boolean, whether to perform learning rate scheduler or not\n",
    "        self.step_size=step                           # Period of learning rate decay\n",
    "        self.gamma = gamma                            # Multiplicative factor of learning rate decay\n",
    "        self.dataset= dataset                         # Dataset name\n",
    "        self.model = \"convnet\"                        # Name of Base Model\n",
    "        self.temperature = temperature                # temperature used in calculating logits\n",
    "        self.max_epoch=max_epoch                      # number of epochs\n",
    "\n",
    "        self.c = c                                    # Curvature of the hyperbolic space\n",
    "        self.hyperbolic = hyperbolic                  # Boolean, if it is hyperbolic or not\n",
    "        self.dim = dim                                # dimenionality of the output vector\n",
    "\n",
    "        self.shot = shot                              # Number of shots in Few shot learning task\n",
    "        self.query = query                            #\n",
    "        self.way = way                                # Number of ways in Few shot learning task\n",
    "        self.validation_way = validation_way          # Number of ways in Few shot learning task for validation set\n",
    "\n",
    "        self.do_clip = do_clip                        # Boolean, whether to perform clipping or not\n",
    "        self.r = r                                    # float, hyperparameter used in CLIP(xE, r)\n",
    "\n",
    "\n",
    "args = Config(dim=512, max_epoch = 5, do_clip = True, r = 1.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "imLdXgEPs3E5"
   },
   "source": [
    "Split training and validation set based on the `Config` for few-shot learning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "U8g8TRexj3so"
   },
   "outputs": [],
   "source": [
    "trainset = CUB(\"train\")\n",
    "train_sampler = CategoriesSampler(trainset.label, 100, args.way, args.shot + args.query)\n",
    "train_loader = DataLoader(dataset=trainset, batch_sampler=train_sampler, num_workers=8, pin_memory=True)\n",
    "\n",
    "valset = CUB(\"val\")\n",
    "val_sampler = CategoriesSampler(valset.label, 500, args.validation_way, args.shot + args.query)\n",
    "val_loader = DataLoader(dataset=valset, batch_sampler=val_sampler, num_workers=8, pin_memory=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "NpgTlZhb6RYL"
   },
   "outputs": [],
   "source": [
    "def lorenz_factor(x, *, c=1.0, dim=-1, keepdim=False):\n",
    "    \"\"\"\n",
    "    Parameters\n",
    "    ----------\n",
    "    x : tensor\n",
    "        point on Klein disk\n",
    "    c : float\n",
    "        negative curvature\n",
    "    dim : int\n",
    "        dimension to calculate Lorenz factor\n",
    "    keepdim : bool\n",
    "        retain the last dim? (default: false)\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    tensor\n",
    "        Lorenz factor\n",
    "    \"\"\"\n",
    "    return 1 / torch.sqrt(1 - c * x.pow(2).sum(dim=dim, keepdim=keepdim))\n",
    "\n",
    "# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
    "\n",
    "# Project a point from Klein model to Poincare model\n",
    "def k2p(x, c):\n",
    "    denom = 1 + torch.sqrt(1 - c * x.pow(2).sum(-1, keepdim=True))\n",
    "    return x / denom\n",
    "\n",
    "# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
    "\n",
    "# Project a point from Poincare model to Klein model\n",
    "def p2k(x, c):\n",
    "    denom = 1 + c * x.pow(2).sum(-1, keepdim=True)\n",
    "    return 2 * x / denom\n",
    "\n",
    "# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
    "\n",
    "def poincare_mean(x, dim=0, c=1.0):\n",
    "    # To calculate the mean, another model of hyperbolic space named Klein model is used.\n",
    "    # 1. point is projected from Poincare model to Klein model using p2k, output x is a point in Klein model\n",
    "    x = p2k(x, c)\n",
    "    # 2. mean is calculated\n",
    "    lamb = lorenz_factor(x, c=c, keepdim=True)\n",
    "    mean = torch.sum(lamb * x, dim=dim, keepdim=True) / torch.sum(lamb, dim=dim, keepdim=True)\n",
    "    # 3. Mean is projected from Klein model to Poincare model\n",
    "    mean = k2p(mean, c)\n",
    "    return mean.squeeze(dim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OWykde95tc7O"
   },
   "source": [
    "### What is the main change on `ProtoNet`?\n",
    "\n",
    "The main difference between the _clipped_ and _normal_ `ProtoNet` lies in the input of the `exp_map`. Therefore, when `args.do_clip` is `True`, everything should be clipped using the `clip`. This results ends in clipping the output of the `self.encoder`, which is the Euclidean embedding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "id": "evNlG8NoiwVQ"
   },
   "outputs": [],
   "source": [
    "class ProtoNet(nn.Module):\n",
    "    def __init__(self, args):\n",
    "        super().__init__()\n",
    "        self.args = args\n",
    "\n",
    "        # Base Model: ConvNet\n",
    "        self.encoder = ConvNet(z_dim=args.dim)\n",
    "\n",
    "        # If working in Hyperbolic Space\n",
    "        if args.hyperbolic:\n",
    "            self.manifold = geoopt.PoincareBall(c=args.c)\n",
    "\n",
    "    def forward(self, data_shot, data_query):\n",
    "        # 1. feed data to the model\n",
    "        proto = self.encoder(data_shot)\n",
    "\n",
    "        \n",
    "        # Hyperbolic Space:\n",
    "        if self.args.hyperbolic:\n",
    "            ###################### CLIP ######################\n",
    "            if args.do_clip:\n",
    "                proto = clip(proto, args.r)\n",
    "            ##################################################\n",
    "\n",
    "            # 2. encoder is Euclidean, output should be projected to Hyperboolic space using exponential map\n",
    "            proto = self.manifold.expmap0(proto)\n",
    "            \n",
    "            if self.training:\n",
    "                proto = proto.reshape(self.args.shot, self.args.way, -1)\n",
    "            else:\n",
    "                proto = proto.reshape(self.args.shot, self.args.validation_way, -1)\n",
    "\n",
    "            # 3. calculate prototypes based on mean of data\n",
    "            proto = poincare_mean(proto, dim=0, c=self.manifold.c.item())\n",
    "            \n",
    "            # 4. query if projected to hyperbolic space too\n",
    "            data_query = self.encoder(data_query)\n",
    "            ###################### CLIP ######################\n",
    "            if args.do_clip:\n",
    "                data_query = clip(data_query, args.r)\n",
    "            ##################################################\n",
    "            data_query = self.manifold.expmap0(data_query)\n",
    "            \n",
    "            # 5. Logits is calculated based on the Hyperbolic distance between data query and proto\n",
    "            logits = (-self.manifold.dist(data_query[:, None, :], proto) / self.args.temperature)\n",
    "\n",
    "        # Euclidean Space\n",
    "        else:\n",
    "            # 2. calculate prototypes based on mean of data\n",
    "            if self.training:\n",
    "                proto = proto.reshape(self.args.shot, self.args.way, -1).mean(dim=0)\n",
    "            else:\n",
    "                proto = proto.reshape(self.args.shot, self.args.validation_way, -1).mean(dim=0)\n",
    "            \n",
    "            # 3. Logits is calculated based on the Euclidean distance between data query and proto\n",
    "            logits = (((self.encoder(data_query)[:, None, :] - proto)**2).sum(dim=-1) / self.args.temperature)\n",
    "        return logits\n",
    "\n",
    "\n",
    "model = ProtoNet(args).to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E-El1RFHIIFe"
   },
   "source": [
    "Once the model is defined, it's time for the training loop. Let's first define *optimizer* and *learning rate scheduler*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "id": "pNGO4PiDIWsK"
   },
   "outputs": [],
   "source": [
    "optimizer = torch.optim.Adam(model.parameters(), lr=args.lr)\n",
    "\n",
    "if args.lr_decay:\n",
    "    lr_scheduler = torch.optim.lr_scheduler.StepLR(optimizer, step_size=args.step_size, gamma=args.gamma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "5WTG2rPBJcfa"
   },
   "outputs": [],
   "source": [
    "# Function to calculate the accuracy given logits and groundtruth labels\n",
    "def count_acc(logits, label):\n",
    "    pred = torch.argmax(logits, dim=1)\n",
    "    if torch.cuda.is_available():\n",
    "        return (pred == label).type(torch.cuda.FloatTensor).mean().item()\n",
    "    else:\n",
    "        return (pred == label).type(torch.FloatTensor).mean().item()\n",
    "# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n",
    "# Class defined to average the values passed to it\n",
    "class Averager:\n",
    "    def __init__(self):\n",
    "        self.n = 0\n",
    "        self.v = 0\n",
    "\n",
    "    def add(self, x):\n",
    "        self.v = (self.v * self.n + x) / (self.n + 1)\n",
    "        self.n += 1\n",
    "\n",
    "    def item(self):\n",
    "        return self.v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MXHCH8bumdZ-"
   },
   "source": [
    "#### Training loop\n",
    "Next step is training the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "U7Y6_MSKI8bg",
    "outputId": "8678f68f-355d-4e3f-bee5-bf0fe92c42f2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 1, train 1/100, loss=1.5794 acc=0.2933\n",
      "epoch 1, train 100/100, loss=1.6932 acc=0.2133\n",
      "epoch 1, val, loss=1.4254 acc=0.3972\n",
      "epoch 2, train 1/100, loss=1.2952 acc=0.4933\n",
      "epoch 2, train 100/100, loss=1.6063 acc=0.2400\n",
      "epoch 2, val, loss=1.4004 acc=0.4254\n",
      "epoch 3, train 1/100, loss=1.4594 acc=0.4000\n",
      "epoch 3, train 100/100, loss=1.6920 acc=0.2133\n",
      "epoch 3, val, loss=1.3755 acc=0.4182\n",
      "epoch 4, train 1/100, loss=1.5255 acc=0.3867\n",
      "epoch 4, train 100/100, loss=1.6323 acc=0.3067\n",
      "epoch 4, val, loss=1.3500 acc=0.4370\n",
      "epoch 5, train 1/100, loss=1.3717 acc=0.4800\n",
      "epoch 5, train 100/100, loss=1.1023 acc=0.6667\n",
      "epoch 5, val, loss=1.3338 acc=0.4510\n"
     ]
    }
   ],
   "source": [
    "for epoch in range(1, args.max_epoch + 1):\n",
    "    if args.lr_decay:\n",
    "        lr_scheduler.step()\n",
    "    model.train()\n",
    "    \n",
    "    tl = Averager()\n",
    "    ta = Averager()\n",
    "\n",
    "    label = torch.arange(args.way).repeat(args.query)\n",
    "    if torch.cuda.is_available():\n",
    "        label = label.type(torch.cuda.LongTensor)\n",
    "    else:\n",
    "        label = label.type(torch.LongTensor)\n",
    "\n",
    "    for i, batch in enumerate(train_loader, 1):\n",
    "        if torch.cuda.is_available():\n",
    "            data, _ = [_.cuda() for _ in batch]\n",
    "        else:\n",
    "            data = batch[0]\n",
    "        p = args.shot * args.way\n",
    "        data_shot, data_query = data[:p], data[p:]\n",
    "        logits = model(data_shot, data_query)\n",
    "        loss = F.cross_entropy(logits, label)\n",
    "        acc = count_acc(logits, label)\n",
    "        \n",
    "        if (i == 1) or (i == len(train_loader)): \n",
    "            print(\"epoch {}, train {}/{}, loss={:.4f} acc={:.4f}\".format(epoch, i, len(train_loader), loss.item(), acc))\n",
    "        \n",
    "        tl.add(loss.item())\n",
    "        ta.add(acc)\n",
    "\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "    \n",
    "    tl = tl.item()\n",
    "    ta = ta.item()\n",
    "\n",
    "    model.eval()\n",
    "\n",
    "    vl = Averager()\n",
    "    va = Averager()\n",
    "\n",
    "    label = torch.arange(args.validation_way).repeat(args.query)\n",
    "    if torch.cuda.is_available():\n",
    "        label = label.type(torch.cuda.LongTensor)\n",
    "    else:\n",
    "        label = label.type(torch.LongTensor)\n",
    "    \n",
    "    with torch.no_grad():\n",
    "        for i, batch in enumerate(val_loader, 1):\n",
    "            if torch.cuda.is_available():\n",
    "                data, _ = [_.cuda() for _ in batch]\n",
    "            else:\n",
    "                data = batch[0]\n",
    "            p = args.shot * args.validation_way\n",
    "            data_shot, data_query = data[:p], data[p:]\n",
    "            logits = model(data_shot, data_query)\n",
    "            loss = F.cross_entropy(logits, label)\n",
    "            acc = count_acc(logits, label)\n",
    "\n",
    "            vl.add(loss.item())\n",
    "            va.add(acc)\n",
    "\n",
    "    vl = vl.item()\n",
    "    va = va.item()\n",
    "    print(\"epoch {}, val, loss={:.4f} acc={:.4f}\".format(epoch, vl, va))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zJGSuTuEm89j"
   },
   "source": [
    "#### Testing function\n",
    "\n",
    "Once the training is complete, it's time to see model's performance on the test split."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "F2CheVhrpB9x"
   },
   "source": [
    "First, let's create test dataloader."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "id": "9Q1Yd1xBv1tB"
   },
   "outputs": [],
   "source": [
    "def compute_confidence_interval(data):\n",
    "    \"\"\"\n",
    "    Compute 95% confidence interval\n",
    "    :param data: An array of mean accuracy (or mAP) across a number of sampled episodes.\n",
    "    :return: the 95% confidence interval for this data.\n",
    "    \"\"\"\n",
    "    a = 1.0 * np.array(data)\n",
    "    m = np.mean(a)\n",
    "    std = np.std(a)\n",
    "    pm = 1.96 * (std / np.sqrt(len(a)))\n",
    "    return m, pm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "id": "l_mN8kGzpKfZ"
   },
   "outputs": [],
   "source": [
    "test_set = CUB(\"test\")\n",
    "test_sampler = CategoriesSampler(test_set.label, 10000, args.validation_way, args.shot + args.query)\n",
    "test_loader = DataLoader(test_set, batch_sampler=test_sampler, num_workers=8, pin_memory=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "x5ysZsZbpWbx",
    "outputId": "7072ec14-db4d-4ff9-bd28-a160db9b9d8a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Acc 0.4033 + 0.0020\n"
     ]
    }
   ],
   "source": [
    "model.eval()\n",
    "\n",
    "ave_acc = Averager()\n",
    "test_acc_record = np.zeros((10000,))\n",
    "\n",
    "label = torch.arange(args.validation_way).repeat(args.query)\n",
    "if torch.cuda.is_available():\n",
    "    label = label.type(torch.cuda.LongTensor)\n",
    "else:\n",
    "    label = label.type(torch.LongTensor)\n",
    "\n",
    "# Testing loop\n",
    "for i, batch in enumerate(test_loader, 1):\n",
    "    if torch.cuda.is_available():\n",
    "        data, _ = [_.cuda() for _ in batch]\n",
    "    else:\n",
    "        data = batch[0]\n",
    "    k = args.validation_way * args.shot\n",
    "    data_shot, data_query = data[:k], data[k:]\n",
    "\n",
    "    logits = model(data_shot, data_query)\n",
    "    acc = count_acc(logits, label)\n",
    "    ave_acc.add(acc)\n",
    "    test_acc_record[i - 1] = acc\n",
    "\n",
    "m, pm = compute_confidence_interval(test_acc_record)\n",
    "print(\"Test Acc {:.4f} + {:.4f}\".format(m, pm))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Acc 0.4160 + 0.0021\n"
     ]
    }
   ],
   "source": [
    "model.eval()\n",
    "\n",
    "ave_acc = Averager()\n",
    "test_acc_record = np.zeros((10000,))\n",
    "\n",
    "label = torch.arange(args.validation_way).repeat(args.query)\n",
    "if torch.cuda.is_available():\n",
    "    label = label.type(torch.cuda.LongTensor)\n",
    "else:\n",
    "    label = label.type(torch.LongTensor)\n",
    "\n",
    "# Testing loop\n",
    "for i, batch in enumerate(test_loader, 1):\n",
    "    if torch.cuda.is_available():\n",
    "        data, _ = [_.cuda() for _ in batch]\n",
    "    else:\n",
    "        data = batch[0]\n",
    "    k = args.validation_way * args.shot\n",
    "    data_shot, data_query = data[:k], data[k:]\n",
    "\n",
    "    logits = model(data_shot, data_query)\n",
    "    acc = count_acc(logits, label)\n",
    "    ave_acc.add(acc)\n",
    "    test_acc_record[i - 1] = acc\n",
    "\n",
    "m, pm = compute_confidence_interval(test_acc_record)\n",
    "print(\"Test Acc {:.4f} + {:.4f}\".format(m, pm))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OpcEYd9zF-3R"
   },
   "source": [
    "When training `ProtoNet` with hyperparameter `r = 1.5`, the performance increases from $40.33$ to $41.60$."
   ]
  }
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